Mohini Joshi

• Led complex data analysis project for NCDOT, under Dr. Lei Zhu, enhancing sampling accuracy by 12% through advanced statistical methodologies
  •Utilized JIRA to manage a project timeline of 1.5 years, tracking over 75 tasks and milestones related to the development of Wi-Fi-based occupancy analytics tools. Ensured that 95% of tasks were completed on time, contributing to the project's overall success.
  •Engineered data integration solutions using Python (improving operational efficiency by streamlining man-hours by 45%), determined trajectory tracking accuracy ~100%.
  •Coordinated with a cross-functional team of 3 members, discussed new ideas and obtained necessary permissions, conducted data collection, cleaning, and analysis on over thousands of Wi-Fi log entries. Presented findings in detailed research paper and presentations. Held bi-weekly sprints, resulting in a 20% increase in team productivity and efficiency

In spearheading strategic planning and execution, I orchestrated a multifaceted project focused on trajectory testing in Wilson for NCDOT, encompassing pedestrian, vehicular, and micro-transit modes. This involved the development of robust testing methodologies to ensure comprehensive data collection and sampling rate analyses, achieving a remarkable 75% rate across three locations near Wilson's Utilities department. By integrating Wi-Fi access point logs and ride app cab data, we attained an impressive ~100% accuracy in trajectory tracking, enabling the development of actionable metrics through meticulous statistical analysis. Additionally, as the lead for comprehensive data analysis and predictions, I oversaw a team of volunteers in a project directed by Dr. Lei Zhu. Leveraging Python and Pandas, we streamlined data processing, reducing man-hours by 45% and enhancing efficiency. Through the application of regression and ANN models, we unearthed significant correlations (~0.60) between Wi-Fi counts, sampling rates, and manual people counts, subsequently improving sampling rate accuracy by 12% through refined data collection methods (in second attempt). These insights not only contributed to a deeper understanding of Wi-Fi detection but also provided valuable feedback for planning transportation services, particularly for handicapped passengers. My proficiency in data analysis, statistical modeling, and effective presentation of findings underscored the importance of leveraging data-driven approaches in enhancing operational efficiency and driving informed decision-making processes.

• Directed a multi-national team in deploying a critical global project for HSBC, automating processes that reduced manual efforts by 7 hours weekly
• Managed cross-functional teams to enhance credit system operations in the Americas, increasing project delivery efficiency by 20%.

• Planning product features, roadmap and MVP breakdown on zSASA Innovation Project
• Implemented Agile methodologies for more efficient project management and team collaboration with engineering and UI/UX teams.
• Presented product updates regularly to various stakeholders even outside the country
• Reduced mainframe workload by 20% and manual-intervention by 10 hours/week.
• 2nd version was patented, received "Best Project - Development"